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Snowflake Cortex Search

snowflake_cortex_search
Read-only

Query a Snowflake Cortex Search Service index to retrieve relevant unstructured text results by service name and search query, with options for result limit and columns.

Instructions

Query a Snowflake Cortex Search Service index over unstructured text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
columnsNo
service_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv1.2.0
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / columns / title
      Removed value: -"Columns"
    • removedInput schema / properties / limit / title
      Removed value: -"Limit"
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • removedInput schema / properties / service_name / title
      Removed value: -"Service Name"
    • removedInput schema / title
      Removed value: -"snowflake_cortex_searchArguments"
    • removedOutput schema / title
      Removed value: -"snowflake_cortex_searchDictOutput"
  2. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds only that this is a semantic search over unstructured text, with no mention of index prerequisites, latency, or how limit/columns affect results. Adequate but thin against a lower annotation-covered bar.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One front-loaded sentence with no filler or redundancy. It is efficient, though its brevity borders on under-specification for a four-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained. However, with four undocumented parameters, no usage guidance, and no behavioral detail beyond the safety hints, the description leaves the agent without enough to invoke the tool confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for all four parameters, so the schema alone gives no meaning for service_name, query, limit, or columns. The description mentions 'query' and 'index' only implicitly and never explains that service_name identifies the target search service or that limit/columns control result shaping.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb (Query) and resource (Snowflake Cortex Search Service index), and the phrase 'over unstructured text' distinguishes it from SQL-oriented siblings like snowflake_query and from the other cortex_* text tools. It stops short of explicitly naming which sibling it replaces, so it lands at 4 rather than 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is given. With siblings such as snowflake_cortex_complete, snowflake_cortex_extract_answer, and snowflake_query, the agent gets no signal on when semantic index search is the right choice versus an LLM completion or a plain SQL query.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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